Non-fragile Filter Design Research Articles

Finite-Time Distributive Non-Fragile Filter Design for Complex Systems with Multiple Delays, Missing Measurements and Dynamic Quantization

Finite-Time Distributive Non-Fragile Filter Design for Complex Systems with Multiple Delays, Missing Measurements and Dynamic Quantization

Event-triggered positive l1-gain non-fragile filter design for positive Markov jump systems

This paper is concerned with the event-triggered positive l 1 -gain non-fragile filter design of positive Markov jump systems. By using the upper and lower bounds of the error vector of system measurement outputs, the positive l 1 -gain filtering system to be designed is transformed into interval uncertain systems. Combining linear Lyapunov functions and linear programming, the positivity and stability of such systems can be obtained. Then, the proposed approach is developed to investigate positive l 1 -gain additive and multiplicative non-fragile filters, respectively. Furthermore, two classes of non-fragile positive filters are proposed for positive Markov jump systems with incomplete measurements and sensors saturation, respectively. Finally, two examples are provided to verify the effectiveness of the proposed design.

Dissipative-based non-fragile filtering for fuzzy networked control systems with switching communication channels

The problem of finite-time dissipative-based non-fragile filter design for a class of discrete-time nonlinear networked control systems subject to randomly occurring parameter uncertainties, external disturbances as well as packet dropouts due to unreliable communication channels and networked induced time-varying delay is discussed. The randomly occurring uncertainties are assumed to satisfy Bernoulli distribution and the considered stochastic variables are mutually independent. Multiple communication channel scenario is taken into account to enhance the data transmission performance and the channel switching phenomena is governed by a Markov chain. The intention here is to design a dissipative-based non-fragile filter for the filtering error system such that it is stochastically finite-time bounded and attains a prescribed dissipative performance attenuation level. Lyapunov stability theory and linear matrix inequality approach are exploited to develop a set of sufficient criterion for the existence of the desired filter. Finally, the filter design framework is applied to the truck-trailer model to demonstrate its effectiveness.

Event-Based Nonfragile H∞ Filter Design for Networked Control Systems with Interval Time-Varying Delay

This paper first investigates the event-triggered nonfragile H∞ filter design for a class of nonlinear NCSs with interval time-varying delay. An event-triggered scheme is addressed to determine sampled data to be transmitted so that network communication resource can be saved significantly. The nonfragile filter design is assumed to include multiplicative gain variations according to the filter’s implement. Under the event-triggered scheme, the filtering error system is modeled as a system with interval time-varying delay. By constructing a new Lyapunov-Krasovskii functional and employing Wirtinger inequality, a sufficient condition is derived, which guarantees that the filtering error system is asymptotically stable with the prescribed H∞ performance. The nonfragile filter parameters are obtained by solving a set of linear matrix inequalities. Two numerical examples are given to show the usefulness and the effectiveness of the proposed method.

Non-fragile filtering for singular Markovian jump systems with missing measurements

In this paper, the issue of an non-fragile filter design is addressed for a class of discrete-time singular Markovian jump systems subject to time-varying delay and missing measurements based on the extended passivity theory. In particular, the missing probability is assumed to be affected by norm-bounded uncertainties. Moreover, the proposed filter design is more general and realistic since it unifies the mode-independent and mode-dependent characteristics in a single framework. By using Lyapunov–Krasovskii stability theory and Abel lemma, a new set of sufficient conditions is established which ensures the stochastic admissibility of the resulting error system with a prescribed disturbance attenuation level. Based on the sufficient conditions, the explicit expression of the desired filter gain matrices is formulated in terms of linear matrix inequalities. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed non-fragile filter design, wherein it is showed that the proposed method yields less conservative results over some existing methods.

Non-fragile filtering for fuzzy stochastic systems over fading channel

This paper investigates the problem of non-fragile filter design for nonlinear stochastic systems subject to channel fading. The nonlinear stochastic systems are represented by the Takagi–Sugeno (T–S) model and the channel fading is described by a random process. By using the Lyapunov method, a sufficient condition which guarantees that the filtering error system is stochastically stable and satisfies the passive performance is established. Then the parameters of the non-fragile filter are obtained by solving linear matrix inequalities (LMIs). Finally, numerical examples are employed to illustrate the effectiveness of the proposed approach.

Nonfragile filtering for discrete-time linear systems in finite-frequency domain

This article investigates the problem of nonfragile filter design for discrete-time linear systems subject to noises with known frequency ranges. Additive interval uncertainty reflecting imprecision in filter implementation is considered. By the aid of generalised KYP lemma, both deterministic and randomised filtering algorithms are proposed to deal with noises in low-, middle- and high-frequency domain, respectively. The proposed nonfragile finite-frequency filters can get a better noise attenuation performance when frequency ranges of noises are known beforehand. An example about F-18 aircraft model is given to illustrate the effectiveness of the proposed algorithms.

Nonfragile $H_{\infty}$ and $H_{2}$ Filter Designs for Continuous-Time Linear Systems Based on Randomized Algorithms

This paper investigates the problem of nonfragile H∞ and H2 filter designs for continuous-time linear systems. Additive filter gain variations to reflect the imprecision in filter implementation are considered. The nonfragile filter design is first formulated as a robust convex optimization problem. Then, both deterministic and randomized algorithms are employed to solve the obtained robust convex optimization problem. Compared with the deterministic algorithm, the proposed randomized one has two advantages: On one hand, it has acceptable computational complexity for systems with high dimensions; on the other hand, it can alleviate the conservatism of deterministic algorithms. Several examples are given to illustrate the effectiveness of the proposed method.